Transcript Health Economics: Hot Topics and Research in Progress Richard E. Nelson, PhD Division of Epidemiology University of Utah School of Medicine Salt Lake City Veterans.

Health Economics: Hot Topics and
Research in Progress
Richard E. Nelson, PhD
Division of Epidemiology
University of Utah School of Medicine
Salt Lake City Veterans Affairs Healthcare System
Presentation Outline
• Brief overview of healthcare costs in the US
• Affordable Care Act
– Oregon Health Insurance Experiment
• Cost of healthcare-acquired infections
– Methods
– Application of these methods to VA data
Economics
• “Economics examines economic events
and arrangements through the lens of
economic theory”
• The study of how individuals,
governments, firms, and nations allocate
scarce resources to satisfy their unlimited
wants
• The study of choices
Health Economic Evaluation
• Bang for the buck
– Inputs (costs)
– Outcomes (benefits)
• Cost-effectiveness
– Achieving objective at least cost, or
– Maximizing benefits from given amount of
resources
Total Healthcare Expenditures
per Capita
$8,000
$7,538
$7,000
$6,000
$5,003
$5,000
$4,627
$4,000
$3,000
$2,902
$2,729 $2,870
$3,129
$3,353 $3,470
$3,677 $3,696 $3,737
$3,970 $4,063 $4,079
$2,000
$1,000
$0
OECD. 2010
Total Health Expenditures as a Share of GDP, 2008
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
16.0%
9.9%
9.1% 9.4%
9.0%
8.7%
8.1% 8.5% 8.5%
11.1% 11.2%
10.4%10.5%10.5% 10.7%
OECD. 2010
Commonwealth Fund 2013
Why Cross-Country Differences in
Healthcare Expenditures
• Administrative costs
– US = 25% of healthcare expenditures
– Other countries = 10-15% of healthcare
expenditures
– Duke University
• 900 beds
• 1,300 billing clerks
– Typical Canadian hospital
• 10 billing clerks
David Cutler, Harvard University
Why Cross-Country Healthcare
Expenditure Differences?
IFHP 2012 Comparative Price Report
Why Cross-Country Healthcare
Expenditure Differences?
IFHP 2012 Comparative Price Report
Why Cross-Country Healthcare
Expenditure Differences?
IFHP 2012 Comparative Price Report
Why Cross-Country Differences in
Healthcare Expenditures
• The same patients get more medical care in
the US
– Ontario, Canada
• 11 hospitals that can do open heart surgery
– Pennsylvania
• 60 hospitals that can do open heart surgery
– Life expectancy and one-year mortality following
heart attack roughly the same
David Cutler, Harvard University
What do we get for our healthcare dollars?
What do we get for our healthcare dollars?
Geographic variation in health care spending
Institute of Medicine 2013
Lowest and Highest Spending Medicare HRRs
Lowest
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Rochester, NY
Stockton, CA
Sacramento, CA
Buffalo, NY
Bronx, NY
Santa Cruz, CA
Santa Rosa, CA
Medford, OR
San Francisco, CA
Salem, OR
Highest
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Miami, FL
McAllen, TX
Monroe, LA
Houston, TX
Alexandria, LA
Lafayette, LA
Shreveport, LA
Baton Rouge, LA
Fort Lauderdale, FL
Metairie, LA
Institute of Medicine 2013
Geographic variation in health care spending
Baicker and Chandra (2008) Health Affairs
Geographic variation in healthcare
spending
• Potential reasons
– Differences in prices paid for similar services
– Differences in illness between regions
– Differences in volume of health care services
received by similar patients
Geographic variation in healthcare
spending
• Why higher volume of care
– More effective care?
– More preference-sensitive care?
– More supply-sensitive care?
Geographic variation in healthcare
spending
• Higher volume of care does not produce
better outcomes for patients
– Worse adherence to evidence-based guidelines1-3
– Worse mortality after heart attack or hip fracture4
– Worse communication among physicians5
– Worse access to care and greater waiting times4
– Worse patient-reported inpatient experience6
1.
2.
3.
4.
5.
Fisher et al (2003) Ann Intern Med
Baicker et al (2004) Health Aff
Fisher et al (2004) Health Aff
Fisher et al (2003) Ann Intern Med
Sivovich et al (2006) Ann Intern
Med
Affordable Care Act
• Signed into law March 23, 2010
• Major components
– Individual mandate
– Employers must offer insurance coverage
– No denying coverage if preexisting condition
– Creating health insurance exchanges
– Expand Medicaid
Affordable Care Act
• Medicaid expansion
– Prior to ACA
• Pregnant women and children < 6 with family incomes
< 133% of FPL
• Children age 6-18 with family incomes < 100% of FPL
• Parents, caretaker relative meeting certain financial
eligibility requirements
• Elderly and disabled individuals who qualify for
Supplementary Security Income
Affordable Care Act
• Medicaid expansion
– After ACA
• All non-Medicare eligible individuals < 65 up to 133%
FPL
– $14,856 for individual in 2012
– $30,657 for family of 4 in 2012
• Federal government pays for expansion
– Supreme Court decision 2012
• Medicaid expansion violates Congress’ spending clause
power
Affordable Care Act
Oregon Health Insurance Experiment
• Oregon Medicaid
– Did not allow new enrollment from 2004-2008
due to budget constraints
– Expanded in 2008
– Excess demand
– So created a lottery
• Treatment group = 29,834
• Control group = 45,088
– Sneak peak at possible impacts of ACA
Oregon Health Insurance Experiment
Results
• Increased hospital admissions
Finkelstein, et al Quarterly Journal of Economics (2012)
Oregon Health Insurance Experiment
Results
• Increased Rx, outpatient encounters
Finkelstein, et al Quarterly Journal of Economics (2012)
Oregon Health Insurance Experiment
Results
• Reduced probability of unpaid medical bill
sent to collection agency
Finkelstein, et al Quarterly Journal of Economics (2012)
Oregon Health Insurance Experiment
Results
• Increased self-reported health and probability
of not screening positive for depression
Finkelstein, et al Quarterly Journal of Economics (2012)
Oregon Health Insurance Experiment
Results
• Increased ED use
Taubman, et al Science (2014)
Oregon Health Insurance Experiment
and ACA
• Summary
– Improvements in self-reported health
– Decreases in financial hardship
– Increases in healthcare utilization
HAI and MRSA
• Healthcare-acquired infections (HAI)
– Infections that result from encounters with healthcare
system
– About 1 in 20 hospitalized patients in US
• Methicillin-resistant Staphylococcus aureus
(MRSA)
– Bacteria resistant to many antibiotics
– One of the leading causes of invasive infections in
healthcare settings
• Bloodstream, pneumonia, and surgical site infections
Accurate cost of HAIs
• Nicholas Graves
– The purpose of cost-of-illness studies for HAIs is to
inform decisions about how to reduce HAIs
• If we know how much they cost, we will know how
much we will save if they are prevented
– 2 measures of cost appropriate for HAIs
1. Excess length of stay
1.
Opportunity costs associated with lost bed-days
2. Variable inpatient costs
1.
Variable vs. fixed costs
Accurate cost of HAIs
1. Excess LOS
2. Variable (and total) inpatient costs
3. Post-discharge costs
Goal of my current research
• Estimate the cost per healthcare-acquired
MRSA infection in the VA using these 3
components:
1. Excess LOS
2. Variable (and total) inpatient costs
3. Post-discharge costs
• And use that estimate to estimate the
budget impact of VA MRSA Prevention
Initiative
Veterans Affairs
MRSA Prevention Initiative
• Began October 2007
• Consisted of a “bundle” of prevention
strategies
– Universal nasal surveillance for MRSA
– Contact precautions for patients colonized or
infected with MRSA
– Hand hygiene
– Institutional change
• HAI prevention is everyone’s responsibility
Estimating cost of MRSA HAI in VA
• Need way of identifying healthcare costs
– VA DSS data
• Activity-based accounting system in VA
• Extracts information from general ledger and VA payroll
system
• Specific job categories, supplies or equipment
• Costs are allocated to cost centers
–
–
–
–
Primary care clinics
Intensive care units
Administration
Environmental services
• Costs are allocated based on employee activities
Estimating cost of MRSA HAI in VA
• Need way of identifying MRSA infections
– ICD-9 code (V09) is not good for MRSA HAIs
• V09 = infection with drug-resistant microorganisms
– Microbiology data
• Unstructured
Schweizer et al ICHE 2011
VA Microbiology Data
Progress to date
1. Excess LOS
– In progress
2. Variable (or total) inpatient costs
– Preliminary results
3. Post-discharge costs
– Preliminary results
1. Impact of HAI on Excess LOS
• Important because each extra bed-day taken up by a
patient with HAI represents opportunity cost for hospital
• Many studies compare total LOS between patients with HAI
and those without
HAI
Patient 1
Admission
Discharge
Patient 2
Admission
Discharge
• But not all of the days are attributable to the HAI
• This leads to “time-dependent bias”
Barnett et al AJE (2009)
Barnett et al Value in Health (2011)
1. Impact of HAI on Excess LOS
• Multi-state models (Beyersmann method)
HAI (1)
l01 ( t )
Admission (0)
lij =
l12 ( t )
l02 ( t )
Discharge/death(2)
number of i ® j transitions
person-time in state i
1. Impact of HAI on Excess LOS
• Using VA data to estimate this
– In progress
2. Impact of HAI on Inpatient Costs
• Many studies compare total inpatient costs
between patients with HAI and those without
HAI
Patient 1
Admission
Discharge
Patient 2
Admission
Discharge
• But not all of the costs are attributable to the HAI
• This leads to “time-dependent bias”
2. Impact of HAI on Inpatient Costs
• Can we identify costs before and after HAI
with VA data?
– Separate observations for each patient-treating
specialty-calendar month
admitday
txspsdt
txspedt
txsp
fy
fp
TotFD
TotFI
TotVD
TotCost
2009-10-29
2009-10-29
2009-10-31
63
2010
1
$1270.52
$17,767.53
$38,508.67
$57,546.72
2009-10-29
2009-10-31
2009-10-31
52
2010
1
$13.83
$195.31
$282.38
$491.52
2009-10-29
2009-11-01
2009-11-04
52
2010
2
$63.47
$1560.92
$1966.30
$3590.69
2009-10-29
2009-11-04
2009-11-05
63
2010
2
$225.60
$1882.73
$2480.43
$4588.76
2009-10-29
2009-11-05
2009-11-12
52
2010
2
$401.53
$7290.23
$9183.70
$16,875.45
2009-10-29
2009-11-12
2009-11-21
22
2010
2
$1089.92
$12,469.61
$15,273.73
$28,833.26
2009-11-01
2009-12-01
5 treating
specialties
txsp 63
txsp 52
txsp 63
txsp 52
txsp 22
6 observations
txsp 63
txsp 52
txsp 63
txsp 52
txsp 22
2. Impact of HAI on Inpatient Costs
• Options to separate pre-HAI costs from postHAI costs
1. Hope that patients with HAI had a new treating
specialty
2. Try to get daily costs for all admitted patients
3. Exploit the quirk that generates a new
observation each month
Option 2
• GEE model on patient-day data
– Gamma distribution
• DSS Daily Cost Resource (DCR)
– Daily inpatient costs
• DSS Production-Level Data
Admitdt
Patient 1
Day 1
Day 2
Admitdt
Patient 2
Day 1
Day 3
Day 4
Day 5
Day 1
Day 6
Day 7
Day 8
Day 9
Day 10
Day 11
HAI
Day 2
Day 3
Dischdt
Day 4
Day 5
Admitdt
Patient 3
Dischdt
HAI
Day 6
Day 7
Dischdt
Day 2
Day 3
Day 4
Day
Day 55
Day 6
Day 8
No HAI
Day 9
Day 10
Day 11
Day 12
Option 3
Month 1
Month 2
X
Patient 1
X
Admitdt
HAI on 1st day of month
Month 1 costs
Patient 2
HAI in
1st
Dischdt
Month 2 costs
X
Admitdt
month
Month 1 costs
Dischdt
Month 2 costs
X
Patient 3
Admitdt
HAI in
2nd
month
Month 1 costs
Dischdt
Month 2 costs
Patient 4
No HAI
Admitdt
Month 1 costs
Dischdt
Month 2 costs
= HAI
Month 1
Month 2
X
Patient 1
X
Admitdt
HAI on 1st day of month
Month 1 costs
Patient 2
HAI in
1st
Dischdt
Month 2 costs
X
Admitdt
month
Dischdt
Month 1 costs
Month 2 costs
X
Patient 3
Admitdt
HAI in
2nd
month
Dischdt
Month 1 costs
Month 2 costs
Patient 4
No HAI
Admitdt
Dischdt
Month 1 costs
X
Patient 5
HAI, 1 month
Month 2 costs
Admitdt
Dischdt
Month 1 costs
Patient 6
No HAI, 1 month
Admitdt
Dischdt
Month 1 costs
= HAI
Option 3
• Methods
– Identify cohort of inpatients at VA hospitals
• Identify those with MRSA HAIs
• Identify those MRSA HAIs that occur on 1st day of
calendar month
– Create longitudinal dataset
• Observation = patient-month
• Treat MRSA HAI as time-varying exposure
2. Impact of HAI on Inpatient Costs
• Patient selection
– Inclusion criteria
• Patients admitted to 1 of 114 VA hospitals nationwide
– 1st hospitalization
• Between Oct 1, 2007 – Sept 30, 2010
• 365 days prior to admission
– Exclusion criteria
• Patients with inpatient stays < 48 hours
• Patients with MRSA positive culture in 365 days prior to
admission
• Patients with MRSA positive surveillance test on index
admission
2. Impact of HAI on Inpatient Costs
Patients meeting inclusion/exclusion criteria
N = 432,874
No MRSA HAI
N = 426,421
MRSA HAI
N = 6,453
1st day of month
N = 208
Middle of month
N = 6245
Results – Multivariable Cost
Regressions
• Model = GEE
• Dependent variable = inpatient cost
• Key independent variable = time-varying MRSA HAI
MRSA HAI as time-varying
exposure
Effect
95% CI
MRSA HAI as non-time
varying exposure
Effect
95% CI
Variable inpatient
$13,893
$10,823
$16,964
$32,513
$28,251 $36,775
Total inpatient
$24,975
$19,530
$30,421
$59,223
$51,697 $66,748
N = 622,386
Note: Regression controlled for the following variables: demographic characteristics, comorbid conditions,
LOS during index hospitalization, primary ICD-9 code for index hospitalization
3. Impact of MRSA HAI on postdischarge costs
• Patient selection
– Inclusion criteria
• Patients admitted to 1 of 114 VA hospitals nationwide
– 1st hospitalization
• Between Oct 1, 2007 – Sept 30, 2010
• 365 days prior to admission
– Exclusion criteria
• Patients with inpatient stays < 48 hours
• Patients with MRSA positive culture in 365 days prior to
admission
• Patients with MRSA positive surveillance test on index
admission
3. Impact of MRSA HAI on postdischarge costs
• Exposure
– MRSA HAI
• MRSA positive clinical culture between 48 hours after
admission and 48 hours after discharge
48 hours
Admission
Inpatient length of stay
48 hours
Discharge
MRSA HAI time window
3. Impact of MRSA HAI on postdischarge costs
• Post-discharge outcomes
– Inpatient costs
• Variable costs
• Total costs
– Outpatient costs
– Pharmacy costs
Inpatient LOS
Admission
Discharge
365 days post-discharge
Post-discharge outcomes time window
3. Impact of MRSA HAI on postdischarge costs
Patients meeting inclusion/exclusion criteria
N = 432,874
No MRSA HAI
N = 426,421
MRSA HAI
N = 6,453
Results – Multivariable Cost
Regressions
• Model = GLM, gamma distribution, log link
• Dependent variable = cost in 365 days post-discharge
• Key independent variable = MRSA HAI
Propensity score matched
subgroup
Full cohort
Effect
95% CI
Effect
95% CI
Outpatient
$466
$86
$845
-$13
-$629
$604
Pharmacy
$958
$514
$1,403
$1,110
$849
$1,371
Total inpatient
$10,917
$9,742
$12,092
$15,194
$12,966
$17,422
Variable inpatient
$5,673
$5,065
$6,282
$7,850
$6,686
$9,013
N = 432,874
Note: Regression controlled for the following variables: demographic characteristics, comorbid
conditions, LOS during index hospitalization, primary ICD-9 code for index hospitalization
Conclusions
• We pay considerably more for healthcare in the
US than other countries do
• Expansion of health insurance coverage under
ACA likely to increase utilization of healthcare
services
• VA is a great environment to study cost of HAI
– Big data
• Cost of MRSA HAIs in VA
– $22,853 using variable inpatient costs
– $41,279 using total inpatient costs
– $59,223 using conventional methods
Thank you
Total Healthcare Expenditures per Capita
1970, 1980, 1990, 2000, 2008
$8,000
$7,000
$6,000
$5,000
$4,000
1970
1980
1990
2000
2008
$3,000
$2,000
$1,000
$-
OECD. 2010
Total Healthcare Expenditures per Capita
1970, 1980, 1990, 2000, 2008
$8,000
$7,000
$6,000
United States
$5,000
Switzerland
$4,000
$3,000
$2,000
$1,000
Canada
OECD Average
Sweden
United
Kingdom
$0
1970 1975 1980 1985 1990 1995 2000 2005
OECD. 2010
Total Health Expenditures as a Share of GDP
1970, 1980, 1990, 2000, 2008
18%
16%
14%
12%
10%
1970
8%
1980
6%
1990
2000
4%
2008
2%
0%
OECD. 2010
Health Expenditures and GDP per Capita
2008
$8,000
USA
$7,000
$6,000
$5,000
$4,000
$3,000
$2,000
Germany
France
Belgium
Italy
U.K.
Spain Japan
Switzerland
Austria
Canada
Norway
Netherlands
Australia
Sweden
$1,000
$0
$25,000
$35,000
$45,000
$55,000
$65,000
GDP Per Capita
OECD. 2010
Health Economics
•
•
•
•
Uncertainty
Asymmetric information
Externalities
Government involvement
Geographic variation in healthcare
spending
• Variation in Healthcare Spending
– Institute of Medicine report, August 2013
– Biggest contributors to variation in Medicare
spending per beneficiary
• Post-acute care services
–
–
–
–
–
Home health agencies
Skilled nursing facilities
Rehabilitation facilities
Long-term care hospitals
Hospices
• Inpatient services
Geographic variation in healthcare
spending
• Variation in Healthcare Spending
– Smallest contributors to variation in Medicare
spending per beneficiary
• Outpatient procedures
• Outpatient visits
• Diagnostic testing
Geographic variation in healthcare
spending
• Variation in Healthcare Spending
– Recommendations
• Not adjust Medicare payments geographically
• Continue to focus on value-based payment reforms
– Patient-centered medical homes
– Bundled payments
– Accountable care organizations
Mean unadjusted outpatient costs
$16,000
$13,427
$12,272
$14,000
$12,000
$10,000
$7,570
$7,111
$8,000
No MRSA HAI
MRSA HAI
$6,000
$4,225 $4,366
$4,000
$2,000
$1,773 $1,710
$0
1 month
3 months
6 months
12 months
Mean unadjusted total inpatient costs
$40,000
$36,030
$35,000
$30,000
$25,000
$22,672
$18,823
$20,000
$11,705
$10,000
$5,000
MRSA HAI
$13,737
$15,000
$2,519
$7,078
$4,413
$0
1 month
3 months
No MRSA HAI
6 months
12 months
Mean unadjusted variable inpatient
costs
$20,000
$18,815
$18,000
$16,000
$14,000
$12,000
$9,842 $9,842
$10,000
$6,143
$6,000
$4,000
$2,000
MRSA HAI
$7,215
$8,000
$1,329
$3,730
$2,314
$0
1 month
3 months
No MRSA HAI
6 months
12 months
Mean unadjusted pharmacy costs
$4,500
$4,146
$4,000
$3,500
$2,850
$3,000
$2,469
$2,500
No MRSA HAI
$2,000
MRSA HAI
$1,554 $1,638
$1,500
$947
$1,000
$500
$672
$360
$0
1 month
3 months
6 months
12 months
1. Impact of HAI on Excess LOS
• Multi-state models (Beyersmann method)
HAI (1)
l01 ( t )
l12 ( t )
Admission (0)
l02 ( t )
Discharge/death(2)
æ 1
1 æ l01 öö
- çç
+
Extra LOS (days) =
ç
÷÷÷
l12 è l01 + l02 l12 è l01 + l02 øø
1
Extra LOS for
pt with HAI
Extra LOS in
state 0
Extra LOS in
state 1
Extra LOS for pt
without HAI
Probability
of infection